About K4AKnowledge 4 All Foundation promotes the spread of knowledge and vivid academic debate to anyone with access to the internet anywhere in the world. It therefore benefits all those interested in academic knowledge and debate, where they do not currently have immediate access to such resources and debate. It also helps to develop more widespread interest in such resources and debate.Knowledge 4 All Foundation Ltd (K4A) is a distributed institute based in London (UK), with two main streams of activities, on one side pioneering Machine Learning methods of pattern analysis, statistical modeling, and computational learning and on the other transform these into technologies for large scale applications in Open Education. It is therefore an advocate of Artificial Intelligence and Big data in Open Education.Knowledge 4 All FoundationK4A_f58c71ec-73bf-11ea-bbb3-7eab1883ea00The Foundation has its main office in London, England, but it operates globally together with a subsidiary in Ljubljana, Slovenia, responsible for infrastructure development as well as the maintenance and development of an exemplar site, videolectures.net.K4A Founding PartnersKnowledge 4 All Foundation was founded in 2009 by lead partners in the PASCAL 2 research project, in partnership with University College London and Jožef Stefan Institute, with a £250k grant from the European Commission via the participation in the TransLectures project.European CommissionUniversity College LondonUCL is consistently placed in the global top 20 across a wide range of university rankings (currently 4th in the QS World University Rankings with a score of 98.9). Furthermore, the Thomson Scientific Citation Index shows that UCL is the 2nd most highly cited European university and 14th in the world. UCL Computer Science had excellent scores in the recent 2014 REF and was ranked first out of all 89 submitted by GPA and the highest percentage (61%) of 4* research (‘of world-leading quality’). In the 2014 Research Excellence Framework (REF) evaluation UCL was ranked in first place for Computer Science, out of 89 Universities assessed, and considerably ahead of other Institutions. 61% of its research work is rated as world-leading (the highest possible category) and 96% of its research work is rated as internationally excellent. UCL researchers in Computer Science and Informatics received a ‘grade point average’ of 3.57 (out of 4) and submitted over 70 staff to be assessed in REF2014. UCL Computer Science has made seminal contributions across the full range of its core strengths and associated 11 research groups and 8 centres, including the Centre for Health Informatics & Multiprofessional Education (CHIME), Biomedical Physics & Biochemical Engineering, and the Centre for Medical Image Computing (CMIC).Jožef Stefan InstituteJožef Stefan Institute is the leading research institution for natural sciences in Slovenia having over 900 researchers within 25 departments working in the areas of computer science, physics, and chemistry and biology. Artificial Intelligence Laboratory, having approx. 40 researchers, is one of the largest European research groups working in the areas of machine learning, data mining, language technologies, semantic technologies and sensor networks. The key research direction is combining modern statistical data analytic techniques with more semantic/logic based knowledge representations and reasoning techniques with the purpose to progress in solving complex problems such as text understanding, large scale probabilistic reasoning, building broad coverage knowledge bases, and dealing with scale. The members have developed several software tools for multimodal data analysis, among others: the Text-Garden suite of text mining tools, the OntoGen system for ontology learning, the Document-Atlas for complex visualization, the AnswerArt system for semantic search over large textual databases, the Enrycher system for semantic enrichment of textual data, SearchPoint system for visual and contextualized Web browsing, XLing for cross-lingual matching and categorization across 100 languages, and Event Registry for global real-time media observatory. Centre for Knowledge Transfer in Information Technologies has approx. ten researchers and technical staff working in the areas of research results dissemination and eLearning. In particular, the centre is well known by portals: VideoLectures.NET with multimedia materials of numerous scientific events, on-line training materials, and collection of tutorials on different scientific fields; ScienceAtlas.ijs.si and IST-World.Org for analysis and visualization of large bibliographic and project databases. The centre is covering management, training and dissemination activities of several EU projects.K4A Board of DirectorsThe Board of Directors are responsible for the overall running of the foundation. The Board is assisted by sub-committees, one of which is an Advisory Board. The Board of Directors appoints members to the Advisory Board at their discretion.K4A TrusteesK4A currently has six trustees, nominated by the founding partners.Davor OrlicDavor Orlic is an MA graduate in Digital Humanities from University College London, co-founded VideoLectures.Net with 25.000 educational videos, created OpeningupSlovenia national educational test bed, established the UNESCO Chair in Open Technologies for OER and Open Education, and UNESCO Chair in Artificial Intelligence. Now managing the K4A Foundation. Works at the intersection of research, technologies, policies and business innovation in education. Has international professional experience in project management and familiar with the Edtech and AI landscape. Managed portfolio of multinational projects exceeding € 10 million (total value) with an extensive experience in grant proposals for research funding. Included in EC experts’ database. He curated the 2nd UNESCO World OER Congress with 500 policy makers and co-designed UNESCO Recommendation on OER, ratified by 195 governments. Launched the first large-scale automatic translation service for open education Translexy and micro-credentials blockchain service for universities Credentify.John Shawe-TaylorJohn Shawe-Taylor (Chairman) has contributed to a number of fields ranging from mathematics of graph theory through cryptography to statistical learning theory and its applications. In graph theory central contributions were to the classification of cubic distance regular graphs, while in cryptography his RSA prime generation algorithm was incorporated into an international standard. However, his main contributions have been in the development of the analysis and subsequent algorithmic definition of principled machine learning algorithms founded in statistical learning theory. This work has helped to drive a fundamental rebirth in the field of machine learning with the introduction of kernel methods and support vector machines. His work in this area has progressed on several parallel fronts: the refinement of the fundamental statistical results that underpin the approach and can be extended to related algorithms and data analysis techniques; the mapping of these applications onto novel domains including work in computer vision, document classification and brain scan analysis; and the extension of learning to improving the representations that are created for learning on different application domains. He has also been instrumental in assembling a series of influential European Networks of Excellence (initially the NeuroCOLT projects and later the PASCAL and PASCAL2 networks). The coordination of these projects has influenced a generation of researchers and promoted the widespread uptake of machine learning in both science and industry that we are currently witnessing. He has also coordinated two influential European research projects, the KerMIT project and most recently the CompLACS (Composing Learning for Artificial Cognitive Systems). Reviews have frequently commented on his effective leadership in both network and other project coordination. John is also UNESCO Chair in Artificial Intelligence.Mitja JermolMitja Jermol received MSc. in 1996 from the Faculty of Mechanical Engineering at the University of Ljubljana. In 1996 he became head of the R&D department in DZS Inc., educational publishing division. His interests have been focused on psychology in learning, knowledge management, digital publishing system, multimedia and the ICT in education. He is head of the Centre for knowledge Transfer at JSI working in the area of eLearning and dissemination and promotion of research results. It operates the VideoLectures.Net website. He has been involved in 15 FP6 and FP7 projects, among others, FP6 ECOLEAD-IP, SEKT-IP, FP7 COIN-IP, ACTIVE-IP and EURIDICE-IP. Before joining the Institute, Mitja was heading the research group for distance education and eLearning at Slovenian major publishing house. Mitja is was conference chair for “Open Course Ware Consortium” Global Conference 2014 and holds the UNESCO Chair on Open Technologies for OER and Open Learning.Colin de la HigueraColin de la Higuera is the author of more than 70 reviewed research papers in the areas of Machine learning, algorithmics and formal language theory, and of a monograph, Grammatical Inference: Learning Automata and Grammars, published in 2010. He has been involved in grammatical inference and machine learning for the past 20 years. He is a trustee of the Knowledge for All foundation, and is involved in the issues of producing open educational resources. In this setting, he acted as chair of the Open Courseware Conference Global held in Ljubljana in 2014. He is head of the COCO project at University of Nantes, former President of the French Computer Science learned society from 2012 to 2015 and current President of the organising and steering committees of Class’Code project which objective is to train teachers and educators, in France, in coding and computational thinking. Colin will be extending the goals of the project to train hundreds of thousands of teachers and education professionals to code and computational thinking via the soon to be UNESCO Chair in technologies for the training of teachers by OER (open educational resources).Dunja MladenićDunja Mladenić is a researcher, project manager and head of the Artificial Intelligence Laboratory at JSI. She is an active researcher in the area of machine learning, text mining and semantic Web. She graduated in Computer Science from the University of Ljubljana and continued as a PhD student focused on Artificial Intelligence. She got her MSc and PhD in Computer Science from the University of Ljubljana in 1995 and 1998 respectively. Among others, Dunja was a long-term visitor at the School of Computer Science, Carnegie Mellon University/USA in 1996/1977 and in 2000/2001. She is the author and editor of several books and papers on machine learning, data/text mining and semantic technologies. She has experience in coordinating EU projects and acting on management board of several EU FP5, FP6 and FP7 projects. She was a program co-chair of ECML 2007, a general chair of ECMLPKDD 2009. Dunja Mladenić is the Slovenian representative in EC Enwise STRATA ETAN Expert Group, she serves as project evaluator and reviewer for various EC programmes.Rayid GhaniRayid Ghani is the Director of the Center for Data Science and Public Policy, Research Director at the Computation Institute and a Senior Fellow at the Harris School of Public Policy at the University of Chicago. He used to be Chief Scientist at Obama for America 2012 campaign focusing on analytics, technology, and data. Senior Research Scientist and Director of Analytics research at Accenture Labs where he led a technology research team focused on applied R&D in analytics, machine learning, and data mining for large-scale & emerging business problems in various industries including healthcare, retail & CPG, manufacturing, intelligence, and financial services. Rayid is a member of IEEE and ACM and has published widely in Machine Learning, Data Mining, and Knowledge Management journals and conferences. He has also organized several machine learning and data mining workshops and has been on Program Committees for a variety of major conferences. He is currently organizing the Data Science for Social Good Conference August 24-25, 2016 in Chicago and running the Data Science for Social Good Fellowship.Marko GrobelnikMarko Grobelnik is an expert in the areas of analysis of large amounts of complex data with the purpose to extract useful knowledge. In particular, the areas of expertise comprise: Data Mining, Text Mining, Information Extraction,Link Analysis, and Data Visualization as well as more integrative areas such as Semantic Web, Knowledge Management and Artificial Intelligence. Apart from research on theoretical aspects of data analysis techniques he has considerable experience in the field of practical applications and development of business solutions based on the innovative technologies. His main achievements are from the field of Text-Mining (analysis of large amounts of textual data), having leading role on scientific and applicative projects funded by European Commission, having projects with industries such as Microsoft Research, British Telecom, New York Times, Siemens, and organizing several international events on the related topics.Machine Learning ResearchersThe Foundation has an extended professional and research community of over 60 members, some of the most important research and development centres in the field of Machine Learning, a research field in Artificial Intelligence in Europe, and a wide Researchers community. K4A has also developed an innovative series of video journals in connection with its members.Machine Learning R&D CentresThe gap is reduced between new trends in education and advanced technologies in artificial intelligence._f58c732c-73bf-11ea-bbb3-7eab1883ea00To promote the spread of knowledge and vivid academic debate to anyone with access to the internet anywhere in the world._f58c741c-73bf-11ea-bbb3-7eab1883ea00KnowledgeAcademic DebateAcademic ResourcesThe Foundation promotes the open access to academic resources (such as video lectures, learning objects, paper, reports, books, and scientific data), together with tools to give users access to these resources and to match them to their needs.Open AccessDiscoverabilityFurthermore, the Foundation aims to help overcome the barriers of limited discoverability and accessibility, as well as enable interaction between users and providers, and among users with common interests.AccessibilityInteractionThe Foundation is a forum where creators, technology developers, managers and users of such resources and tools can meet to actively promote the free availability and distribution of such content and tools, as well as develop strategies for fostering interactions between users and providers and among users with common interests.Common InterestsMachine LearningPioneer Machine Learning methods of pattern analysis, statistical modeling, and computational learning._f58c7502-73bf-11ea-bbb3-7eab1883ea001The unique ways in which K4A supports its 1000+ researchers and 62 member institutions is by co-funding more than 260 events, 60+ machine learning challenges, 20.000 academic video lectures and creating machine learning tools and software.Events, Challenges & LecturesCo-fund events, machine learning challenges, and academic video lectures._f58c75de-73bf-11ea-bbb3-7eab1883ea001.1K4A has organised, funded and co-funded around 250 events (conferences, symposiums, workshops and seminars) to bring together the community of technology users with those researchers who have developed tools, proofs of concept and demonstrations of feasibility. These events are also binge used for public outreach purposes and mark the beginning of massive video recording which preceded MOOCs. This activity lead to the funding, creation and support of VideoLectures.Net, an award winning website with 20.000 academic talks.Tools & SoftwareCreate machine learning tools and software._f58c76b0-73bf-11ea-bbb3-7eab1883ea001.2While retaining some of the structuring elements and mechanisms (such as the Pump-Priming and Challenges programmes) of its predecessor NoE, PASCAL1 and PASCAL 2, K4A refocuses the institute towards the emerging challenges created by the ever expanding applications of adaptive systems technology and their central role in the development of artificial cognitive systems of different scales. This is mainly combined towards open education and Open Educational Resources (OER). Learning technology is key to, for instance, making robots more versatile, effective and autonomous, and to endowing machines with advanced interaction capabilities. K4A responds to these challenges not only through the research topics it addresses but also by engaging in technology transfer through an Industrial Club to effect rapid deployment of the developed technologies into a wide variety of applications. In addition, its Challenges, Pump Prime and Harvest programmes, counting altogether more than 60 projects, provides opportunities for close collaboration between academic and industry researchers. Other noteworthy outreach activities include curriculum development, brokerage of expertise, public outreach, and liaison with relevant R&D projects. Furthermore, K4A has adopted an open membership policy allowing for active inclusion in Network activities, of researchers working at non-beneficiary institutions.EducationTransform ML methods into technologies for large scale applications in Open Education._f58c77a0-73bf-11ea-bbb3-7eab1883ea002The aim of the Foundation is therefore to combine open education and machine learning and to reduce the current gap between new trends in education, on the one hand, and advanced technologies in artificial intelligence, on the other, with the ultimate goal of securing the future of open education. K4A explores the new and rapidly-changing global trends in higher education, and how intelligent and advanced technologies have influenced education in general. It also promotes the use of machine learning in many relevant application domains such as:ML & Big Data StandardsLeverage standard developments in Machine Learning and Big Data to promote the use of machine learning in Advanced developments in ICT and Education_f58c7890-73bf-11ea-bbb3-7eab1883ea002.1Machine VisionPromote the use of machine learning in Technologies for Open Educational Resources_f58c7976-73bf-11ea-bbb3-7eab1883ea002.2SpeechPromote the use of machine learning in Open and Massive Learning Environments_f58c7a70-73bf-11ea-bbb3-7eab1883ea002.3HapticsPromote the use of machine learning in Innovative Business Models in Publishing_f58c7b60-73bf-11ea-bbb3-7eab1883ea002.4Brain-Computer InterfacePromote the use of machine learning in open innovation, science and education in a systemic way_f58c7c50-73bf-11ea-bbb3-7eab1883ea002.5Computer/Human InteractionLeverage user-modeling for computer human interaction to promote the use of machine learning in accessible, open national digital learning repositories_f58c7d4a-73bf-11ea-bbb3-7eab1883ea002.6Multimodal IntegrationPromote the use of machine learning in open frameworks and standards for interoperability and portability_f58c7e3a-73bf-11ea-bbb3-7eab1883ea002.7Natural Language ProcessingPromote the use of machine learning to develop accessible, open national digital learning repositories_f58c7f2a-73bf-11ea-bbb3-7eab1883ea002.8Information RetrievalPromote the use of machine learning to enable personalization, and collaboration_f58c807e-73bf-11ea-bbb3-7eab1883ea002.9Textual Information AccessPromote the use of machine learning for better connectivity between formal, and non-formal and informal learning_f58c8178-73bf-11ea-bbb3-7eab1883ea002.102020-03-31https://www.k4all.org/about-k4a/OwenAmburOwen.Ambur@verizon.net